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Method, system and device for predicting storage device performance

A storage device and prediction method technology, applied in faulty hardware testing methods, faulty computer hardware detection, machine learning, etc., to achieve the effects of highlighting substantive features, reducing workload, and enhancing practicability

Active Publication Date: 2022-05-31
SUZHOU METABRAIN INTELLIGENT TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The performance value of the storage device is related to the number of links selected, the RAID level, the number of disks included in the RAID, the number of created LUNs, and the number of concurrent parameters under the condition that the hardware remains unchanged. During the process of performance tuning of the storage device , each parameter adjustment will affect the level of performance. In general, it is necessary to repeatedly debug and combine experience to select the optimal storage performance configuration. There is no direct theoretical basis and plan to refer to

Method used

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  • Method, system and device for predicting storage device performance
  • Method, system and device for predicting storage device performance
  • Method, system and device for predicting storage device performance

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Embodiment Construction

[0064] The specific embodiments of the present invention will be described below with reference to the accompanying drawings.

[0065] like figure 1 The shown method for predicting the performance of a storage device includes the following steps:

[0066] S1: Build a storage device environment and collect test data.

[0067] The test data includes: the RAID level of the storage device, the number of disks included in the RAID, the number of output links, the number of LUNs created in each RAID, the concurrent number of the test performance, and the performance test result.

[0068] S2: According to the test data representation method required for building the AdaBoost iterative algorithm model, the collected test data is constructed as a data sample feature space vector.

[0069] Perform performance tests on each storage device to obtain performance data under different configurations. The representations of different configurations, performance results, and data samples are...

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Abstract

A storage device performance prediction method, system and device proposed by the present invention can predict the performance of storage devices through the AdaBoost iterative algorithm model, and can effectively use various data samples obtained when developing and testing storage devices, and obtain them after machine learning The AdaBoost iterative algorithm model can provide users with better configuration solutions for storage devices and reduce the workload of developers and testers for tuning storage devices, which is very practical.

Description

technical field [0001] The present invention relates to the technical field of storage device testing, and more particularly to a method, system and device for predicting the performance of a storage device. Background technique [0002] With the rapid development of scientific computing and various network applications, more and more information is generated by human beings, which makes the storage of data more and more concerned by people, thus making the storage components occupy the position in the entire computer system. More and more important, storage has shifted from a single disk, tape to disk array, and then developed to the current popular storage network. The demand for large-scale data applications continues to emerge, and massive data and its applications have also become a new development direction. Data storage has had a huge impact on people's work and life, and the performance improvement of the storage devices used has also been improved. Naturally, more ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62G06N20/00G06F11/22
CPCG06N20/00G06F11/2273G06F18/2148
Inventor 李闯李玲侠
Owner SUZHOU METABRAIN INTELLIGENT TECH CO LTD